Al ethics- Best practices

The workshop enables you to understand the foundations/ building blocks of AI and to understand how they can be used to solve complex business problems.
 
Concepts
  • What is AI
  • What is the value proposition of AI projects
  • What is an AI project – Key characteristics of an AI project
  • AI problems:   Classification, Regression, Recommendation etc   
Data strategy
  • Understanding data
  • Visualising data
  • Understanding feature engineering
  • AI project team composition
 
Business case
  • AI business readiness and maturity   
  • AI projects – causes for success
  • AI projects causes for failure
  • Creating the AI project business case
  • How to define incremental wins
  • How to create competitive advantage
  • Understanding the state of the art(industry KPIs and benchmarks)
  • Model evaluation
Integration and deployment
  • Deployment considerations (DevOps and CI/CD)
  • Monitoring AI projects 
  • Scaling an AI project
  • Integration with other systems (ex ERP)
  • Big data strategy
  • Cloud strategy
  • Agile integration

How to manage AI projects

The workshop enables you to understand the foundations/ building blocks of AI and to understand how they can be used to solve complex business problems.
 
Concepts
  • What is AI
  • What is the value proposition of AI projects
  • What is an AI project – Key characteristics of an AI project
  • AI problems:   Classification, Regression, Recommendation etc   
Data strategy
  • Understanding data
  • Visualising data
  • Understanding feature engineering
  • AI project team composition
 
Business case
  • AI business readiness and maturity   
  • AI projects – causes for success
  • AI projects causes for failure
  • Creating the AI project business case
  • How to define incremental wins
  • How to create competitive advantage
  • Understanding the state of the art(industry KPIs and benchmarks)
  • Model evaluation
Integration and deployment
  • Deployment considerations (DevOps and CI/CD)
  • Monitoring AI projects 
  • Scaling an AI project
  • Integration with other systems (ex ERP)
  • Big data strategy
  • Cloud strategy
  • Agile integration

Intellectual Property Rights and Artificial Intelligence

The workshop enables you to understand the foundations/ building blocks of AI and to understand how they can be used to solve complex business problems.
 
Concepts
  • What is AI
  • What is the value proposition of AI projects
  • What is an AI project – Key characteristics of an AI project
  • AI problems:   Classification, Regression, Recommendation etc   
Data strategy
  • Understanding data
  • Visualising data
  • Understanding feature engineering
  • AI project team composition
 
Business case
  • AI business readiness and maturity   
  • AI projects – causes for success
  • AI projects causes for failure
  • Creating the AI project business case
  • How to define incremental wins
  • How to create competitive advantage
  • Understanding the state of the art(industry KPIs and benchmarks)
  • Model evaluation
Integration and deployment
  • Deployment considerations (DevOps and CI/CD)
  • Monitoring AI projects 
  • Scaling an AI project
  • Integration with other systems (ex ERP)
  • Big data strategy
  • Cloud strategy
  • Agile integration

AI Business Strategy for Competitive advantage

The workshop enables you to understand the foundations/ building blocks of AI and to understand how they can be used to solve complex business problems.
 
Concepts
  • What is AI
  • What is the value proposition of AI projects
  • What is an AI project – Key characteristics of an AI project
  • AI problems:   Classification, Regression, Recommendation etc   
Data strategy
  • Understanding data
  • Visualising data
  • Understanding feature engineering
  • AI project team composition
 
Business case
  • AI business readiness and maturity   
  • AI projects – causes for success
  • AI projects causes for failure
  • Creating the AI project business case
  • How to define incremental wins
  • How to create competitive advantage
  • Understanding the state of the art(industry KPIs and benchmarks)
  • Model evaluation
Integration and deployment
  • Deployment considerations (DevOps and CI/CD)
  • Monitoring AI projects 
  • Scaling an AI project
  • Integration with other systems (ex ERP)
  • Big data strategy
  • Cloud strategy
  • Agile integration

AI for government and policy makers

The workshop enables you to understand the foundations/ building blocks of AI and to understand how they can be used to solve complex business problems.
 
Concepts
  • What is AI
  • What is the value proposition of AI projects
  • What is an AI project – Key characteristics of an AI project
  • AI problems:   Classification, Regression, Recommendation etc   
Data strategy
  • Understanding data
  • Visualising data
  • Understanding feature engineering
  • AI project team composition
 
Business case
  • AI business readiness and maturity   
  • AI projects – causes for success
  • AI projects causes for failure
  • Creating the AI project business case
  • How to define incremental wins
  • How to create competitive advantage
  • Understanding the state of the art(industry KPIs and benchmarks)
  • Model evaluation
Integration and deployment
  • Deployment considerations (DevOps and CI/CD)
  • Monitoring AI projects 
  • Scaling an AI project
  • Integration with other systems (ex ERP)
  • Big data strategy
  • Cloud strategy
  • Agile integration